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一种用于胃癌预后和免疫治疗的新型缺氧-免疫特征:来自批量和单细胞RNA测序的见解

A Novel Hypoxia-Immune Signature for Gastric Cancer Prognosis and Immunotherapy: Insights from Bulk and Single-Cell RNA-Seq.

作者信息

Nguyen Mai Hanh, Ta Hoang Dang Khoa, Nguyen Doan Phuong Quy, Le Viet Huan, Le Nguyen Quoc Khanh

机构信息

International Ph.D. Program in Cell Therapy and Regenerative Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan.

Pathology and Forensic Medicine Department, 103 Military Hospital, Hanoi 151000, Vietnam.

出版信息

Curr Issues Mol Biol. 2025 Jul 16;47(7):552. doi: 10.3390/cimb47070552.

Abstract

: Hypoxia and immune components significantly shape the tumor microenvironment and influence prognosis and immunotherapy response in gastric cancer (GC). This study aimed to develop hypoxia- and immune-related gene signatures for prognostic evaluation in GC. : Transcriptomic data from TCGA-STAD were integrated with hypoxia- and immune-related genes from InnateDB and MSigDB. A prognostic gene signature was constructed using Cox regression analyses and validated on an independent GSE84437 cohort and single-cell RNA dataset. We further analyzed immune cell infiltration, molecular characteristics of different risk groups, and their association with immunotherapy response. Single-cell RNA-seq data from the TISCH database were used to explore gene expression patterns across cell types. : Five genes (, , , , ) were identified. The risk score effectively stratified patients by prognosis, with the high-risk group showing lower overall survival and lower T-cell expression. The gene signature had an association with immune suppression, mutation, EMT features, and poorer response to immunotherapy. Gene signature, especially was enriched in fibroblasts. : We developed a robust hypoxia- and immune-related gene signature that predicts prognosis and may help guide immunotherapy strategies for GC patients.

摘要

缺氧和免疫成分显著塑造肿瘤微环境,并影响胃癌(GC)的预后和免疫治疗反应。本研究旨在开发用于GC预后评估的缺氧和免疫相关基因特征。:来自TCGA-STAD的转录组数据与来自InnateDB和MSigDB的缺氧和免疫相关基因整合。使用Cox回归分析构建预后基因特征,并在独立的GSE84437队列和单细胞RNA数据集中进行验证。我们进一步分析了免疫细胞浸润、不同风险组的分子特征及其与免疫治疗反应的关联。来自TISCH数据库的单细胞RNA测序数据用于探索跨细胞类型的基因表达模式。:鉴定出五个基因(,,,,)。风险评分有效地按预后对患者进行分层,高危组显示总体生存率较低且T细胞表达较低。基因特征与免疫抑制、突变、EMT特征以及对免疫治疗的较差反应相关。基因特征,尤其是在成纤维细胞中富集。:我们开发了一种强大的缺氧和免疫相关基因特征,可预测预后并可能有助于指导GC患者的免疫治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1062/12293835/18feb0c94793/cimb-47-00552-g001.jpg

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